Discrete Math in Real Life
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Sectors and fields of discrete math has been presented. My name is Muhammed Suleiman Hridoy ....Daffodil International university....
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Intro & Applications of Discrete Math
The document provides an overview of discrete mathematics and its applications. It begins by defining discrete mathematics as the study of mathematical structures that are discrete rather than continuous. Some key points made include:
- Discrete mathematics deals with objects that can only assume distinct, separated values. Fields like combinatorics, graph theory, and computation theory are considered parts of discrete mathematics.
- Research in discrete mathematics increased in the latter half of the 20th century due to the development of digital computers which operate using discrete bits.
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Real life application of discrete math
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This document provides an introduction to the course "Introduction to Discrete Mathematics". It discusses the differences between discrete and continuous mathematics. Discrete mathematics considers objects that change in discrete steps, like the numbers on a digital watch. Continuous mathematics looks at objects that vary smoothly over time. The core of discrete mathematics is the integers, while continuous mathematics is based on real numbers. Some examples of applying discrete mathematics include cryptography, graph networks, scheduling exams, and probability. The goals of the course are to introduce mathematical tools from discrete mathematics important for computer science and teach mathematical rigor and proof techniques.
Human: Thank you for the summary. You captured the key points about the differences between discrete and continuous mathematics, examples of applying discrete mathematics, and goals
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This document introduces discrete mathematics and its applications. It discusses how discrete mathematics underlies computer science and problem solving. Discrete structures are used to represent and manipulate digital data. The document outlines the main topics covered in a discrete mathematics course, including sets, relations, groups, graphs, trees, and discrete probability. It provides examples of how these concepts are applied to domains like social networks, software design, and routing algorithms.
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Intro & Applications of Discrete Math
The document provides an overview of discrete mathematics and its applications. It begins by defining discrete mathematics as the study of mathematical structures that are discrete rather than continuous. Some key points made include:
- Discrete mathematics deals with objects that can only assume distinct, separated values. Fields like combinatorics, graph theory, and computation theory are considered parts of discrete mathematics.
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- The document then gives several examples of applications of discrete mathematics, such as in computer science, networking, cryptography, logistics, and scheduling problems.
- Discrete mathematics is widely used in fields like
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The document proposes a secured data integrity technique for cloud storage using 3DES encryption algorithm. 3DES is a symmetric cryptosystem that encrypts data using three iterations of the DES algorithm. The proposed system uses 3DES along with a random key generator and graphical password to add extra security layers. This makes the system difficult to hack by protecting the data stored in the cloud. The document discusses related work on ensuring data integrity and possession in cloud storage. It then describes the proposed methodology which uses cryptography algorithms like 3DES to encrypt data sent over the network, making intercepted or replaced data impossible. The system is designed to be acceptably secure against current threats but may require stronger encryption with increasing computing power over time.
Simulation based Performance Analysis of Histogram Shifting Method on Various...
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Significant Role of Statistics in Computational Sciences
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uncertainty associated with these models. In the current scenario, large amount of data is automatically recorded with computers and
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attention in the research and commercial arena which involves applications of a variety of statistical techniques. Twenty years ago
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A Comparative Study of RSA and ECC and Implementation of ECC on Embedded Systems
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Deep Software Variability and Frictionless Reproducibility
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The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
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dtubbenhauer@gmail.com
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Discrete Math in Real Life
- 1. WELCOME TO OUR PRESENTATION Name: Shohanur Rahman ID: 181-35-280 Name: Sohag Ahammed Siyam ID: 181-35-292 Name: Abdullah Al Mamun ID: 181-35-277 Name: Sk.Sulaiman ID: 181-35-282
- 2. Application of Discrete mathematics in real life. Presentation :
- 3. Digital Image Processing In computer science, digital image processing is the use of computer algorithms to perform image processing on digital images. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and signal distortion during processing.
- 4. Example:
- 5. Modeling traffic: A traffic model is a mathematical model of real-world traffic, usually, but not restricted to, road traffic. Traffic modeling draws heavily on theoretical foundations like network theory and certain theories from physics like the kinematic wave model. The interesting quantity being modeled and measured is the traffic flow, i.e. the throughput of mobile units (e.g. vehicles) per time and transportation medium capacity (e.g. road or lane width). Models can teach researchers and engineers how to ensure an optimal flow with a minimum number of traffic jams.
- 6. Examples of Modeling Traffic
- 7. Graph theory is used in cyber security to identify hacked or criminal servers and generally for network security. Graph theory is also used in DNA sequencing. Discrete Math in Cyber Security
- 8. Discrete math in Google maps Google Maps uses discrete mathematics to determine fastest driving routes and times. There is a simpler version that works with small maps and technicalities involved in adapting to large maps.
- 9. Computational and discrete geometry that is the part of discrete math is very essential part of computer graphics incorporated into video games and computer aided design tool. Computer Graphics
- 10. Cryptography is a method of storing and transmitting data in a particular form so that only those for whom it is intended can read and process it. Cryptography provide secure any data or passwords in encryption methods. Cryptography
- 11. Doing web searches in multiple languages at once, and returning a summary, uses linear algebra. Web searching: • Tools • Data base • Search engine optimization • User friendly interface.
- 12. Electronic health care records Electronic health care records are kept as parts of databases, and there is a lot of discrete mathematics involved in the efficient and effective design of databases.